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Cellular automata (CA) are simple models that can simulate complex processes in both space and time. A CA consists of six defining components: a framework, cells, a neighborhood, rules, initial conditions, and an update sequence. CA models are simple, nominally deterministic yet capable of showing phase changes and emergence, map easily onto the data structures used in geographic information systems, and are easy to implement and understand. This has contributed to their popularity for applications such as measuring land use changes and monitoring disease spread, among many others.
- Origins and Development
- CA Principles and Theory
- CA in Geography
- Advantages and Limitations of CA
Cellular automata - A regular framework of cells, each in one of a finite number of states. The states of all cells in the framework are updated simultaneously in discrete time steps during which the state of each cell is changed according to a set of rules that depend on the state of the cell and those of its neighbors at the previous time step.
- Describe what a cellular automaton is and what its key components are
- Discuss how CA evolved through its development in mathematics, computer science, and geography
- Identify CA principles and patterns using the game of Life and simple software
- Summarize how CA has been adapted for modeling in geography using GIS
- Critique CA for modeling geographical systems
- Demonstrate how to examine the CA research literature
- Examine the Wikipedia entry for Conway’s Game of Life. What are examples of some of the static forms that can emerge in the Game of Life?
- What are the six elements that form a CA? Which are parts of the geographic input data, and which are parts of the CA model itself?
- Define a complex system and what is meant by emergence. Why are CA’s good tools for understanding complexity?
- How does a CA integrate both space and time?
- How fast can change propagate across a region when modeled by CA? What are the implications of this rate of dynamics for modeling geographical systems?
- How did CA move from computer science and physics into geography, and why?
- Research five papers written in the last 5 years that use CA models in geography. What parts of the discipline was CA applied to in each?
- Batty, M. (2005). Cities and Complexity: Understanding Cities with Cellular Automata, Agent-Based Models, and Fractals. Cambridge, MA: The MIT Press.
- Benenson, I. and Torrens, P. (2004). Geosimulation: Automata-based Modeling of Urban Phenomena, New York: J. Wiley
- Burks, E. (1972). Essays on Cellular Automata. Chicago: University of Illinois Press.
- CA Repository http://uncomp.uwe.ac.uk/genaro/CA_repository.html
- Engelen, G., White, R. Uljee, I., and Drazan, P. (1995). Using cellular automata for integrated modelling of socio-environmental systems. Environmental Monitoring and Assessment, 34, 2, 203-214.
- J.H. Conway's game of Life. FAQ (http://alife.santafe.edu/alife/topics/cas/ca-faq/ca-faq.html). Usenet newsgroups: news:comp.theory.cell-automata, news:comp.theory.self-org-sys.
- Third International Conference/Workshop on Integrating GIS and Environmental Modeling (1996) http://www.geo.upm.es/postgrado/CarlosLopez/materiales/cursos/www.ncgia....